Abstract

This experiment assessed the ability of an on-line dual energy x-ray absorptiometer (DEXA) installed at a commercial abattoir to determine commercial cut weights in lamb carcases at abattoir chain-speed. 200 lamb carcases were scanned using a DEXA that was trained to predict the computed tomography determined proportions of fat, lean, and bone. Models were then trained using hot carcase weight and, DEXA fat% value or GR tissue depth to predict cut weight. Results from validation tests of DEXA models demonstrated excellent precision for predicting cut weight, in most cases describing more than 85% of the variation, and RMSE values that represented between 5 and 13% of the average weight of each cut. For most cuts these weight predictions were superior to those informed by GR tissue depth. This precision was maintained upon validation. Additional analyses utilised pixel information from the fore, saddle, and hind sections of DEXA images. This further enhanced the predictive power of cut weight models.

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